Abstract. This study investigates a method for best member selection of a Limited area model Ensemble Prediction System (LEPS) with the goal to increase quantitative precipitation forecast. A case study that occurred between 22-24 May 2002 over Calabria, southern Italy, is discussed.

Mediterranean storms often develop under upper level disturbances which are usually associated with high values of potential vorticity. Anomalously high values of potential vorticity can be identified by the METEOSAT water vapor channel centered around 6.3 μm because they are associated with dark band on the METEOSAT image. This signature offers a chance to identify the upper level disturbance that can be exploited in data void countries as Calabria.

The working hypothesis is that the uncertainty in the representation of the upper-level disturbance has a major impact on the precipitation forecast. This issue is utilized in an ensemble forecast where member forecasts are compatible with the analysis and forecast errors. These members are grouped in five clusters by a hierarchical clustering technique which utilizes the height of the dynamical tropopause to compute distances between members. Therefore the members of a cluster have a similar representation of the upper level disturbance. For each cluster a representative member is selected and its pseudo water vapor image is compared with the corresponding METEOSAT 7 water vapor image at a specific time, antecedent to the rain occurrence over Calabria. The subjective evaluation of the comparison allows to gain physical insight in the storm evolution and to select representative members which are more in agreement with the METEOSAT image.

Results, even if for a case study, show the feasibility of the methodology that, if confirmed by further investigations, could be valuable in data void countries as the central Mediterranean basin.